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Python Integration with ClickHouse Connect


ClickHouse Connect is a suite of Python packages providing interoperability with a wide range of Python applications. The three primary components are:

  • A low level driver in the package clickhouse_connect.driver. This package includes a basic client that handles all ClickHouse Connect requests to the ClickHouse Server, as well assorted helper classes and utility functions.
  • A limited SQLAlchemy dialect in the package clickhouse_connect.cc_sqlalchemy. This package focuses implements query/cursor functionality, and does not generally support SQLAlchemy DDL and ORM operations. (SQLAlchemy is targeted toward OLTP databases, and we recommend more specialized tools and frameworks to manage the ClickHouse OLAP database.)
  • An Apache Superset EngineSpec in the clickhouse_connect.cc_superset. This package will automatically add a ClickHouse Connect Superset connector when ClickHouses Connect is installed. This EngineSpec supports all core Superset query functionality, but does not currently support certain advanced features such as file upload to a ClickHouse table.

Requirements and Compatibility

PythonPlatform¹ClickHouseSQLAlchemy²Apache Superset
2.x, <3.7Linux (x86)<22.3³🟡<1.3<1.4
3.7.xLinux (Aarch64)22.3.x1.3.x1.4.x
3.8.xMacOS (x86)22.4-22.6³🟡1.4.x1.5.x
3.9.xMacOs (M1)22.7.x>=2.x2.0.x

¹ClickHouse Connect has been tested against the listed platforms. Because it can run in pure Python (without the optional C optimizations), it is likely to work on most recent Python installations.

²Again SQLAlchemy support is limited primarily to query functionality. The full SQLAlchemy API is not supported.

³ClickHouse Connect has been tested against all currently supported ClickHouse versions. Because it uses the HTTP protocol, it should also work correctly for most other versions of ClickHouse, although there may be some incompatibilities with certain advanced data types.


Install ClickHouse Connect from PyPI via pip:

pip install clickhouse-connect

ClickHouse Connect can also be installed from source by checking out the GitHub repository and running pip install . in the project root directory.

Support Policy

ClickHouse Connect is currently in beta and only the current beta release is actively supported. Please update to the latest version before reported any issues. Issues should be filed in the GitHub project.
Future releases of ClickHouse Connect are guaranteed to be compatible with actively supported ClickHouse versions at the time of release (generally the three most recent stable and two most recent lts releases).

Basic Usage

Gather your connection details

To connect to ClickHouse with HTTP(S) you need this information:

  • The HOST and PORT: typically, the port is 8443 when using TLS or 8123 when not using TLS.

  • The DATABASE NAME: out of the box, there is a database named default, use the name of the database that you want to connect to.

  • The USERNAME and PASSWORD: out of the box, the username is default. Use the username appropriate for your use case.

The details for your ClickHouse Cloud service are available in the ClickHouse Cloud console. Select the service that you will connect to and click Connect:

ClickHouse Cloud service connect button

Choose HTTPS, and the details are available in an example curl command.

ClickHouse Cloud HTTPS connection details

If you are using self-managed ClickHouse, the connection details are set by your ClickHouse administrator.

Establish a connection

There are two examples shown for connecting to ClickHouse:

  • Connecting to a ClickHouse server on localhost.
  • Connecting to a ClickHouse Cloud service.

Use a ClickHouse Connect client instance to connect to a ClickHouse server on localhost:

import clickhouse_connect

client = clickhouse_connect.get_client(host='localhost', username='default', password='password')

Use a ClickHouse Connect client instance to connect to a ClickHouse Cloud service:


Use the connection details gathered earlier. ClickHouse Cloud services require TLS, so use port 8443.

import clickhouse_connect

client = clickhouse_connect.get_client(host='', port=8443, username='default', password='your password')

Interact with your database

To run a ClickHouse SQL command, use the client command method:

client.command('CREATE TABLE new_table (key UInt32, value String, metric Float64) ENGINE MergeTree ORDER BY key')

To insert batch data, use the client insert method with a two-dimensional array of rows and values:

row1 = [1000, 'String Value 1000', 5.233]
row2 = [2000, 'String Value 2000', -107.04]
data = [row1, row2]
client.insert('new_table', data, column_names=['key', 'value', 'metric'])

To retrieve data using ClickHouse SQL, use the client query method:

result = client.query('SELECT max(key), avg(metric) FROM new_table')
Out[13]: [(2000, -50.9035)]